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Availability of emergency obstetric and newborn care (EmONC) is a strong supply side measure of essential health system capacity that is closely and causally linked to maternal mortality reduction and fundamentally to achieving universal health coverage. The World Health Organization's indicator "Availability of EmONC facilities" was prioritized as a core indicator to prevent maternal death. The indicator focuses on whether there are sufficient emergency care facilities to meet the population need, but not all facilities designated as providing EmONC function as such. This study seeks to validate "Availability of EmONC" by comparing the value of the indicator after accounting for key aspects of facility functionality and an alternative measure of geographic distribution. This study takes place in four subnational geographic areas in Argentina, Ghana, and India using a census of all birthing facilities. Performance of EmONC in the 90 days prior to data collection was assessed by examining facility records. Data were collected on facility operating hours, staffing, and availability of essential medications. Population estimates were generated using ArcGIS software using WorldPop to estimate the total population, and the number of women of reproductive age (WRA), pregnancies and births in the study areas. In addition, we estimated the population within two-hours travel time of an EmONC facility by incorporating data on terrain from Open Street Map. Using these data sources, we calculated and compared the value of the indicator after incorporating data on facility performance and functionality while varying the reference population used. Further, we compared its value to the proportion of the population within two-hours travel time of an EmONC facility. Included in our study were 34 birthing facilities in Argentina, 51 in Ghana, and 282 in India. Facility performance of basic EmONC (BEmONC) and comprehensive EmONC (CEmONC) signal functions varied considerably. One facility (4.8%) in Ghana and no facility in India designated as BEmONC had performed all seven BEmONC signal functions. In Argentina, three (8.8%) CEmONC-designated facilities performed all nine CEmONC signal functions, all located in Buenos Aires Region V. Four CEmONC-designated facilities in Ghana (57.1%) and the three CEmONC-designated facilities in India (23.1%) evidenced full CEmONC performance. No sub-national study area in Argentina or India reached the target of 5 BEmONC-level facilities per 20,000 births after incorporating facility functionality yet 100% did in Argentina and 50% did in India when considering only facility designation. Demographic differences also accounted for important variation in the indicator's value. In Ghana, the total population in Tolon within 2 hours travel time of a designated EmONC facility was estimated at 99.6%; however, only 91.1% of women of reproductive age were within 2 hours travel time. Comparing the value of the indicator when calculated using different definitions reveals important inconsistencies, resulting in conflicting information about whether the threshold for sufficient coverage is met. This raises important questions related to the indicator's validity. To provide a valid measure of effective coverage of EmONC, the construct for measurement should extend beyond the most narrow definition of availability and account for functionality and geographic accessibility.

BackgroundA global midwifery shortage hampers the goal of ending preventable maternal/newborn mortality and stillbirths. Whether current measures of midwifery workforce adequacy are valid is unknown. We compare two measures of density and distribution of midwifery professionals to assess their consistency, and explore how incorporating midwifery scope, competency, and the adjusting reference population impacts this critical metric.Methods and findingsWe collected a census of midwives employed in eligible facilities in our study settings, (422 in Ghana; 909 in India), assessed the number practicing within the scope of work for midwifery professionals defined in the International Labor Organization International Standard Classification of Occupations, and whether they reported possessing the ICM essential competencies for basic midwifery practice. We altered the numerator, iteratively narrowing it from a simple count to include data on scope of practice and competency and reported changes in value. We altered the denominator by calculating the number of midwives per 10,000 total population, women of reproductive age, pregnancies, and births and explored variation in the indicator. Across four districts in Ghana, density of midwives decreased from 8.59/10,000 total population when counting midwives from facility staffing rosters to 1.30/10,000 total population when including only fully competent midwives by the ICM standard. In India, no midwives met the standard, thus the midwifery density of 1.37/10,000 total population from staffing rosters reduced to 0.00 considering competency. Changing the denominator to births vastly altered subnational measures, ranging from ~1700% change in Tolon to ~8700% in Thiruvallur.ConclusionOur study shows that varying underlying parameters significantly affects the value of the estimate. Factoring in competency greatly impacts the effective coverage of midwifery professionals. Disproportionate differences were noted when need was estimated based on total population versus births. Future research should compare various estimates of midwifery density to health system process and outcome measures.

Background A global midwifery shortage hampers the goal of ending preventable maternal/newborn mortality and stillbirths. Whether current measures of midwifery workforce adequacy are valid is unknown. We compare two measures of density and distribution of midwifery professionals to assess their consistency, and explore how incorporating midwifery scope, competency, and the adjusting reference population impacts this critical metric. Methods and findings We collected a census of midwives employed in eligible facilities in our study settings, (422 in Ghana; 909 in India), assessed the number practicing within the scope of work for midwifery professionals defined in the International Labor Organization International Standard Classification of Occupations, and whether they reported possessing the ICM essential competencies for basic midwifery practice. We altered the numerator, iteratively narrowing it from a simple count to include data on scope of practice and competency and reported changes in value. We altered the denominator by calculating the number of midwives per 10,000 total population, women of reproductive age, pregnancies, and births and explored variation in the indicator. Across four districts in Ghana, density of midwives decreased from 8.59/10,000 total population when counting midwives from facility staffing rosters to 1.30/10,000 total population when including only fully competent midwives by the ICM standard. In India, no midwives met the standard, thus the midwifery density of 1.37/10,000 total population from staffing rosters reduced to 0.00 considering competency. Changing the denominator to births vastly altered subnational measures, ranging from ~1700% change in Tolon to ~8700% in Thiruvallur. Conclusion Our study shows that varying underlying parameters significantly affects the value of the estimate. Factoring in competency greatly impacts the effective coverage of midwifery professionals. Disproportionate differences were noted when need was estimated based on total population versus births. Future research should compare various estimates of midwifery density to health system process and outcome measures.

Understanding place-based contributors to health requires geographically and culturally diverse study populations, but sharing location data is a significant challenge to multisite studies. Here, we describe a standardized and reproducible method to perform geospatial analyses for multisite studies. Using census tract-level information, we created software for geocoding and geospatial data linkage that was distributed to a consortium of birth cohorts located throughout the USA. Individual sites performed geospatial linkages and returned tract-level information for 8810 children to a central site for analyses. Our generalizable approach demonstrates the feasibility of geospatial analyses across study sites to promote collaborative translational research.

Active commuting to school increases children’s daily physical activity. The built environment is associated with children’s physical activity levels in cross-sectional studies. This study examined the role of the built environment on the out- comes of a “walking school bus” study. Geographical information systems was used to map out and compare the built envi- ronments around schools participating in a pilot walking school bus randomised controlled trial, as well as along school routes. Multi-level modelling was used to determine the built environment attributes associated with the outcomes of active commuting to school and accelerometer-determined moderate-to-vigorous physical activity (MPVA). There were no differ- ences in the surrounding built environments of control (n = 4) and intervention (n = 4) schools participating in the walking school bus study. Among school walking routes, park space was inversely associated with active commuting to school (β = -0.008, SE = 0.004, P = 0.03), while mixed-land use was positively associated with daily MPVA (β = 60.0, SE = 24.3, P = 0.02). There was effect modification such that high traffic volume and high street connectivity were associated with greater moderate-to-vigorous physical activity. The results of this study suggest that the built environment may play a role in active school commuting outcomes and daily physical activity.

National trends indicate that children and adolescents are not achieving sufficient levels of physical activity. Combining global positioning system (GPS) technology with accelerometers has the potential to provide an objective determination in locations where youth engage in physical activity. The aim of this study was to identify the optimal methods for collecting combined accelerometer and GPS data in youth, to best locate where children spend time and are physically active. A convenience sample of 24 mid-school children in Massachusetts was included. Accelerometers and GPS units were used to quantify and locate childhood physical activity over 5 weekdays and 2 weekend days. Accelerometer and GPS data were joined by time and mapped with a geographical information system (GIS) using ArcGIS software. Data were collected in winter, spring, summer in 2009-2010, collecting a total of 26,406 matched datapoints overall. Matched data yield was low (19.1% total), regardless of season (winter, 12.8%; spring, 30.1%; summer, 14.3%). Teacher-provided, pre-charged equipment yielded the most matched (30.1%; range: 10.1-52.3%) and greatest average days (6.1 days) of data. Across all seasons, children spent most of their time at home. Outdoor use patterns appeared to vary by season, with street use increasing in spring, and park and playground use increasing in summer. Children spent equal amounts of physical activity time at home and walking in the streets. Overall, the various methods for combining GPS and accelerometer data provided similarly low amounts of combined data. No combined GPS and accelerometer data collection method proved superior in every data return category, but use of GIS to map joined accelerometer and GPS data can demarcate childhood physical activity locations.